A new research paper shows the approach performs significantly better than the random-walk forecasting method.

Overview: Interpretability tools make machine learning models more transparent by displaying how each feature influences ...

Artificial intelligence-driven algorithms can be used to better forecast models for natural disasters, saving lives and protecting property by rapidly analyzing massive data sets and identifying ...

As solar energy plays an increasing role in the global power supply, ensuring accurate forecasts of photovoltaic (PV) power generation is critical for balancing energy demand and supply. A new study ...

A recent study, “Picking Winners in Factorland: A Machine Learning Approach to Predicting Factor Returns,” set out to answer a critical question: Can machine learning techniques improve the prediction ...

Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...

Forecasting inflation has become a major challenge for central banks since 2020, due to supply chain disruptions and economic uncertainty post-pandemic. Machine learning models can improve forecasting ...

Vassili Kitsios is a senior research scientist at CSIRO, a co-chair of the Machine Learning for Climate and Weather Working Group of the Australian Climate Community Earth System Simulator National ...

DUBLIN--(BUSINESS WIRE)--The "AI and Machine Learning in Business Market: Market Size, Trends, Opportunities and Forecast By Industry Vertical, Application, Component, Region, By Country: 2020-2030" ...